• Cat-intel
  • MedIntelliX
  • Resources
  • About Us
  • Hero Background
    English
    Chinese
    French
    Japanese
    Korean
    German
    Spanish

    Applied AI in Agriculture Market Analysis

    ID: MRFR/ICT/10647-HCR
    128 Pages
    Shubham Munde
    October 2025

    Applied AI in Agriculture Market Research Report: By Technology (Machine Learning, Computer Vision, and Predictive Analytics), By Offering (Software and AI-as-a-Service), By Application (Drone Analytics and Precision Farming) By Region (North America, Europe, Asia-Pacific, Middle East & Africa, and South America), Market Forecast Till 2035.

    Share:
    Download PDF ×

    We do not share your information with anyone. However, we may send you emails based on your report interest from time to time. You may contact us at any time to opt-out.

    Applied AI in Agriculture Market Infographic
    $ 4,950.0
    $ 5,950.0
    $ 7,250.0

    Market Analysis

    In-depth Analysis of Applied AI in Agriculture Market Industry Landscape

    The Applied AI in Agriculture Market is a dynamic sector driven by various market factors that converge to influence its growth and development processes. One critical factor driving this industry includes the need for sustainable agricultural practices that can produce enough food to cater for large global populations. To deal with issues such as climate change, resource limitations and labor inadequacy; applied artificial intelligence (AI) would help optimize farming activities therefore increasing productivity through precision agriculture.

    The foundation of technological innovation lies at the heart of the Applied AI in Agriculture Market. Innovations in AI algorithms, machine learning models and sensor technology contribute to the development of intelligent solutions that can analyze vast amounts of agricultural data. The market responds to innovations such as AI-driven crop monitoring, predictive analytics for yield optimization, and robotic automation in farming by providing data-driven insights and automation capabilities to key participants within agriculture.

    The global economic environment has a substantial impact on the Applied AI in Agriculture Market. Economic patterns may bring about changes in considering investments like those made by farmers, governments or even agribusinesses who need to incorporate various technologies using AI for their operations. This leads to an increasing number of investments into innovative approaches during economic growth periods which offer higher efficiency and better returns. Conversely, economic downturns may influence a more cautious approach, affecting the pace of adoption and investment in AI technologies for agriculture.

    Regulatory dynamics as well as compliance issues are significant drivers within the Applied AI in Agriculture Market. As farming becomes increasingly reliant upon artificial intelligence systems including regulatory frameworks involving data privacy rights use of land etc., will become applicable. Companies that develop or deploy Ai into this industry must follow these rules to show they ethically use these systems.

    In the Applied AI in Agriculture Market, competitive landscape is a key influencer. The competition is stiff with different companies offering AI solutions for agriculture. When selecting their AI technologies, farmers and agricultural businesses consider the degree of accuracy in AI models, ability to adapt to various farming practices, ease of use, and price-effectiveness very vital. The market is dynamic since it revolves around ever-changing farm challenges along with continuous innovation.

    Market shape is determined by customer preferences as well as industry trends. As the possibilities of AI to change agriculture are increasingly realized by stakeholders in the industry, there has been an integration between this technology and precision farming equipment, farm management software that enables farmers control crops better and supply chain optimization tools that reduce waste. In order for providers of AI strategies in agriculture to stay ahead in competition, they must be capable of adapting to changing expectations held by their clients as well as changing forces within the industry.

    Market Summary

    As per Market Research Future Analysis, the Applied AI in Agriculture Market is projected to grow from USD 3,324.84 Million in 2025 to USD 43494.66 Million by 2035, with a CAGR of 29.32% during the forecast period. The market was valued at USD 2571.02 Million in 2024. Key applications include real-time insights, crop health monitoring, and automated irrigation, enhancing harvest quality and efficiency. The North America region is leading in growth due to the demand for real-time data, while Europe is focusing on robotics integration to address labor shortages. Asia is rapidly adopting AI and IoT for smart farming solutions.

    Key Market Trends & Highlights

    The Applied AI in Agriculture Market is characterized by significant technological advancements and increasing adoption across regions.

    • Market growth from USD 3,324.84 Million in 2025 to USD 33,633.29 Million by 2034.
    • Machine Learning holds the largest market share due to affordability and cloud-based platforms.
    • Drones are crucial for data gathering, enhancing precision agriculture capabilities.
    • North America leads in market growth driven by real-time data requirements.

    Market Size & Forecast

    2024 Market Size USD 2571.02 Million
    2035 Market Size USD 43494.66 Million
    CAGR 29.32%

    Major Players

    Microsoft, IBM, Google, Amazon.com, Inc., Deere & Company, Vision Robotics Corporation, DroneDeploy, PrecisionHawk, AGCO Corporation

    Market Trends

    Use of Machine learning

    In the artificial intelligence driven market, machine learning has become a critical technology with broad applications. Machine learning algorithms allow the analysis of huge data sets gathered from drones, satellites, and sensors providing farmers with insight for informed decision making. These algorithms are able to identify trends, patterns, as well as anomalies within data regarding soil quality, crop health, weather conditions, and more. Machine learning's capability of predicting is specifically valuables. By training models on real- and historical-time data, farmers can anticipate factors such as pest infestations, outbreaks, and optimal planting times.

    Adoption of Drones

    Drones play crucial roles in the artificial intelligence driven agriculture market. Equipped with innovative cameras and sensors, drones provide a bird eye view, allowing farmers to gather high-resolution data and imagery. AI processes this data for monitoring crop health, identifying pests, as well as access irrigation required. Drones provide quick and comprehensive data gathering over large areas, an advantage in precision agriculture.

    The integration of artificial intelligence in agriculture is poised to enhance productivity and sustainability, reflecting a transformative shift in farming practices that could redefine food security.

    U.S. Department of Agriculture

    Applied AI in Agriculture Market Market Drivers

    Market Charts

    Rising Demand for Food Security

    The Global Applied AI in Agriculture Market Industry is significantly influenced by the increasing demand for food security. As the global population continues to rise, the need for sustainable agricultural practices becomes paramount. AI applications, such as predictive analytics and automated farming solutions, are being adopted to enhance crop yields and reduce waste. This trend is expected to drive the market towards a valuation of 43.5 USD Billion by 2035. The integration of AI technologies in agriculture not only addresses food scarcity but also promotes sustainable practices, aligning with global efforts to ensure food security for future generations.

    Technological Advancements in AI

    The Global Applied AI in Agriculture Market Industry is experiencing rapid growth driven by technological advancements in artificial intelligence. Innovations such as machine learning and computer vision are enhancing precision agriculture practices. For instance, AI-powered drones and sensors are being utilized to monitor crop health and optimize resource use. This technological evolution is projected to contribute to the market's expansion, with a valuation of 2.48 USD Billion in 2024, indicating a strong foundation for future growth. As these technologies become more accessible, they are likely to revolutionize farming practices globally, leading to increased efficiency and productivity.

    Government Initiatives and Support

    Government initiatives play a crucial role in the Global Applied AI in Agriculture Market Industry. Various countries are implementing policies and funding programs to encourage the adoption of AI technologies in agriculture. For example, initiatives aimed at promoting smart farming practices and research into AI applications are gaining traction. These efforts are likely to bolster market growth, as they provide farmers with the necessary resources and knowledge to implement AI solutions effectively. The support from governments can accelerate the transition towards AI-driven agriculture, fostering innovation and enhancing productivity on a global scale.

    Sustainability and Environmental Concerns

    Sustainability and environmental concerns are increasingly shaping the Global Applied AI in Agriculture Market Industry. As awareness of climate change and resource depletion grows, there is a pressing need for sustainable agricultural practices. AI technologies are being leveraged to optimize resource use, reduce chemical inputs, and minimize environmental impact. For instance, AI-driven irrigation systems can significantly reduce water consumption while maintaining crop health. This alignment with sustainability goals is likely to attract investment and drive market growth, as stakeholders recognize the potential of AI to contribute to environmentally friendly farming practices.

    Market Segment Insights

    Global Air Start Unit Market- Segment Insights

    Applied AI in Agriculture Market - Technology Insights

    The Applied AI in Agriculture Market, in this report, has been segmented based on Technology into Machine Learning, Computer Vision, and Predictive Analytics. Machine learning holds the largest share, this is due to factors such as the cost of machine learning (ML) technology becoming more affordable, making it easier for farmers to adopt. There are also a number of cloud-based ML platforms available that make it easy for farmers to get started with ML. Machine learning (ML) can be used to make sense of the vast amounts of data that agriculture generates.

    This data can include weather data, soil data, and crop data. ML can be used to identify patterns and trends in this data that can be used to improve crop yields, reduce the use of pesticides and fertilizers, and conserve water. Machine learning (ML) can be used to automate tasks that are typically done by farmers, such as monitoring crops, managing irrigation, and detecting pests and diseases. This can free up farmers' time so they can focus on other tasks, such as planning and marketing.

    FIGURE 2: GLOBAL Applied AI in Agriculture MARKET, BY Technology, 2022 VS 2032 (USD MILLION)

    Source: Secondary Research, Primary Research, Market Research Future Database, and Analyst Review

    Applied AI in Agriculture Market - Offering Insights

    The Applied AI in Agriculture Market, in this report, has been segmented based on Software and AI-as-a-Service. The Software segments hold the largest share due to the increasing adoption of precision agriculture. Precision agriculture is a farming practice that uses data and technology to optimize crop yields and efficiency. This includes using sensors to collect data on soil conditions, weather, and crop health, and then using AI to analyze this data to make better decisions about planting, irrigating, fertilizing, and harvesting.

    Applied AI in Agriculture Market - Application Insights

    The Applied AI in Agriculture Market, in this report, has been segmented based on Drone Analytics and Precision Farming. Drone’s analytics hold the largest share. Drone analytics is a process of collecting data on crops and soil conditions using drones. This data can be used to identify problems early, such as pests and diseases, and to make better decisions about planting, irrigating, and fertilizing.

    Get more detailed insights about Applied AI in Agriculture Market Research Report – Forecast till 2034

    Regional Insights

    The North America market is witnessing major growth because of the growing requirement for real time data in the agriculture market. This technology enables them to access critical information about livestock, crops, as well as environmental conditions. By leveraging artificial intelligence powered drones, powered sensors, and other monitoring tools, farmers can collect data on factors such as pest infestations, soil moisture, and temperature. The capability for gathering as well as analyzing real-time data allow farmers to make good decisions. For example, AI is capable of predicting disease outbreaks allowing farmers to take preventive steps before the problem escalates.

    The utilization of artificial intelligence-powered predictive analytics allows farmers to anticipate issues as well as implement timely measures, thereby reducing crop losses as well as optimizing yields. Moreover, artificial intelligence driven systems can monitor as well as manage fertilizer application, crop health, and irrigation, leading to resource efficiency as well as sustainable agriculture practices. As the agriculture industry embraces artificial intelligence capabilities, the market for artificial intelligence in agriculture in North America region the market for AI in agriculture is soaring.

    FIGURE 3: Applied AI in Agriculture Market SIZE BY REGION 2022 VS 2032

    Applied AI in Agriculture Market SIZE BY REGION 2022 VS 2032

    Source: Secondary Research, Primary Research, Market Research Future Database, and Analyst Review

    The Europe Applied AI in the agriculture market is witnessing substantial growth, specifically in agriculture robotics. The integration of AI with robotics is transforming the agricultural landscape by enabling advanced solutions to withstand challenges. Robotics in agriculture, integrated by AI, have a broad range of applications such as precision spraying, automated planting, precision spraying, monitoring livestock, and harvesting. A major driver of this growth in the adoption of robotics is due to labor shortages in the agriculture industry. The deployment of artificial intelligence driven robots can majorly minimize the dependency on manual labor for intense and time-consuming work.

    These robots can work continuously, even in adverse conditions or weather, contributing to enhancing productivity and efficiency. Moreover, artificial intelligence allows robots to operate autonomously along with making real time decisions which are based on data from cameras, sensors, and other sources. This intelligence level allows for accurate and targeted actions, reducing wastage of resources as well as environmental impact. The integration between robotics and AI also leads to enhanced data gathering along with analysis, offering insight farmers can use for optimizing their practices and improving crop yields.

    As Europe's agriculture sector is continuously adopting robotics the market in the region is experiencing substantial growth.

    In Asia, the application of AI in agriculture is quickly gaining momentum and transforming the industry. The region's broad agricultural landscapes as well as a major population make artificial intelligence a valuable tool for solving complex challenges faced in agriculture sectors. Asia is experiencing remarkable growth in the application of AI in agriculture, with a major emphasis on IOT. The convergence of IOT and AI is reshaping the agriculture sector by providing growers and farmers innovative tools for data driven decision making as well as resource management.

    The implementation of Internet of Things devices in agriculture is resulting in the creation of smart farms. These farms are installed with devices and sensors that gather real time data on factors for instance with devices and sensors that gather real time data on various factors such as temperature, humidity, and crop health. Artificial intelligence algorithms analyze data to offer insight into optimal irrigation schedules, planting times, as well as pest control measures.

    The growth of the Internet of Things in Asia’s agricultural sectors is driven by factors for instance required to meet the demand of increasing population, ensure food security, and optimize resource utilization. By harnessing the power of IOT and AI, farmers can obtain higher yields, and minimize waste and inputs such as pesticides and water. Moreover, IOT-enabled devices enable remote monitoring as well as control empowering farmers to manage their operations more effectively. These technologies are specifically important in regions having limited access to resources.

    As the integration of IOT and AI continues to expand around the Asian agriculture industry, the region stands to gain enhanced, sustainability, resilience, and productivity in face of evolving agricultural challenges.

    Key Players and Competitive Insights

    The Applied AI in the Agriculture market is highly competitive, with a number of established players competing for market share. The market is primarily driven by the The growing adoption of cloud computing. There are several domestic, regional, and global players operating in the Applied AI in Agriculture market who continuously strive to gain a significant share of the overall market. During the study, MRFR has analyzed some of the major players in the Air Start Unit market who have contributed to the market growth.

    These include Some notable players in the Applied AI in Agriculture market include Microsoft, IBM, Google, Amazon.com, Inc., Deere & Company., TechTarget, Vision Robotics Corporation., DroneDeploy., PrecisionHawk, and AGCO Corporation., Others.

    Among these, Microsoft is a prominent solution provider of wide range of AI solutions for agriculture. The company offers a range of AI solutions that can be used to detect pests and diseases in crops, and to track livestock. IBM is another AI solution that can be used to monitor crops, predict yields, and manage irrigation. Similarly, Deere & Company's AI solutions can be used to monitor crops and drive autonomously.

    Key Companies in the Applied AI in Agriculture Market market include

    Industry Developments

    May 2022, The Alliance for a Green Revolution in Africa (AGRA) and Microsoft have expanded their partnership to advance digital agricultural transformation in Africa. The partnership, which was formalized through a Memorandum of Understanding (MoU) signed on the sidelines of the World Economic Forum in Davos in 2022, builds on previous work between AGRA and Microsoft that focused on supporting AGRA's digital transformation efforts to improve food security in Africa.

    December 2022 Amazon Web Services (AWS), a subsidiary of Amazon.com, Inc., announced eight new capabilities for Amazon SageMaker, its fully managed machine learning (ML) service. Amazon SageMaker allows developers, data scientists, and business analysts to build, train, and deploy ML models quickly and easily.

    September 2022 DroneDeploy and Corteva Agriscience announced a partnership to help farmers make better management decisions year-round. Corteva operates one of the world's largest agricultural drone fleets, and DroneDeploy is a leading provider of drone software. Together, the two companies will offer farmers a suite of tools that can be used to monitor crops, identify problems, and optimize yields.

    Future Outlook

    Applied AI in Agriculture Market Future Outlook

    The Applied AI in Agriculture Market is projected to grow at a 29.32% CAGR from 2025 to 2035, driven by advancements in precision farming, data analytics, and automation technologies.

    New opportunities lie in:

    • Develop AI-driven crop monitoring systems to enhance yield predictions.
    • Implement autonomous machinery for efficient planting and harvesting processes.
    • Create AI-based pest management solutions to minimize chemical usage and increase sustainability.

    By 2035, the market is expected to be a cornerstone of agricultural innovation and efficiency.

    Market Segmentation

    Applied AI in Agriculture Market - Offering Outlook

    • Software
    • AI-as-a-Service

    Applied AI in Agriculture Market - Regional Outlook

    • US
    • Canada
    • Mexico

    Applied AI in Agriculture Market - Technology Outlook

    • Machine Learning
    • Computer Vision
    • Predictive Analytics

    Applied AI in Agriculture Market - Application Outlook

    • Drone Analytics
    • Precision Farming

    Report Scope

    Report Attribute/Metric Details
    Market Size 2024 2571.15 (USD Million)
    Market Size 2025 3324.84 (USD Million)
    Market Size 2035 43494.66 (USD Million)
    Compound Annual Growth Rate (CAGR) 29.32% (2025 - 2035)
    Report Coverage Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
    Base Year 2024
    Market Forecast Period 2025 - 2035
    Historical Data 2019 - 2023
    Market Forecast Units USD Million
    Segments Covered Technology, Offering, and Application
    Geographies Covered Europe, North America, Asia-Pacific, Middle East & Africa, and South America
    Countries Covered The U.S, Germany, Canada, U.K., Italy, France, Spain, Japan, China, Australia, India, South Korea, and Brazil
    Key Companies Profiled Microsoft, IBM, Google, Amazon.com, Inc., Deere & Company., TechTarget, Vision Robotics Corporation., DroneDeploy., PrecisionHawk, and AGCO Corporation., Others.
    Key Market Opportunities The need to improve crop quality The decreasing cost of AI solutions
    Key Market Dynamics The growing adoption of cloud computing The increasing adoption of precision agriculture

    Market Highlights

    Author

    Shubham Munde
    Research Analyst Level II

    She holds an experience of about 6+ years in market research and business consulting, working under the spectrum of information communication technology, telecommunications and semiconductor domains. aarti conceptualizes and implements a scalable business strategy and provides strategic leadership to the clients. her expertise lies in market estimation, competitive intelligence, pipeline analysis, customer assessment, etc.

    Leave a Comment

    Latest Comments

    John Doe
    john@example.com

    This is a great article! Really helped me understand the topic better.

    Posted on July 23, 2025, 10:15 AM
    Jane Smith
    jane@domain.com

    Thanks for sharing this. I’ve bookmarked it for later reference.

    Posted on July 22, 2025, 7:45 PM

    FAQs

    How much is Applied AI in Agriculture market?

    Applied AI in Agriculture market was valued at USD 2571.15 Million in 2024.

    What is the growth rate of the Applied AI in Agriculture market?

    The global market is projected to grow at a CAGR of 29.32% during the forecast period, 2025-2034.

    Which region held the largest market share in the Applied AI in Agriculture market?

    North America had the largest share of the global market.

    Who are the key players in the Applied Artificial Intelligence in Agriculture market?

    The key players in the market are Microsoft, IBM, Google, Amazon.com, Inc. and Deere & Company.

    1. EXECUTIVE SUMMARY
      1. Market Attractiveness
        1. Global Applied AI In Agriculture Market, by Technology
        2. Global Applied
        3. Global Applied AI In Agriculture
    2. MARKET INTRODUCTION
      1. Definition
      2. Scope
      3. Market Structure
      4. Key Buying Criteria
    3. RESEARCH METHODOLOGY
      1. Research
      2. Primary Research
      3. Secondary Research
      4. Market
      5. Forecast Model
      6. List of Assumptions
    4. MARKET
      1. Introduction
      2. Drivers
        1. The growing adoption
        2. The increasing adoption of precision agriculture
        3. Driver impact analysis
      3. Restraints
        1. High Cost of artificial
        2. Restraint impact analysis
        3. The need to improve crop quality
        4. The decreasing
      4. Challenges
        1. Shortage of skilled labor
      5. Covid-19 Impact Analysis
      6. Impact Analysis of COVID-19
        1. Economic Impact
        2. Impact on Market Demand of
    5. MARKET FACTOR ANALYSIS
      1. Value Chain
      2. Porter’s Five Forces Model
        1. Bargaining Power of Buyers
        2. Threat of Substitutes
        3. Intensity of
    6. GLOBAL APPLIED AI IN AGRICULTURE MARKET, BY TECHNOLOGY
      1. Machine Learning
      2. Computer Vision
      3. Predictive
    7. GLOBAL APPLIED AI IN AGRICULTURE MARKET, BY OFFERING
      1. Software
      2. AI-as-a-Service
    8. GLOBAL APPLIED
      1. Introduction
      2. Drone
      3. Precision Farming
    9. GLOBAL APPLIED AI IN AGRICULTURE MARKET
      1. Introduction
      2. North
        1. Market Estimates & Forecast, by Country, 2019-2032
        2. Market Estimates
        3. Market Estimates & Forecast,
        4. US
        5. Canada
        6. Mexico
      3. Europe
        1. Market Estimates
        2. Market Estimates & Forecast,
        3. Market Estimates & Forecast, by Offering,
        4. Market Estimates & Forecast, by Application, 2019-2032
        5. UK
        6. Germany
        7. France
        8. Italy
        9. Spain
      4. Asia-Pacific
        1. Market Estimates & Forecast, by Country, 2019-2032
        2. Market
        3. Market Estimates
        4. Market Estimates & Forecast,
        5. China
        6. Japan
        7. South Korea
        8. Rest of Asia-Pacific
      5. Rest of the World
        1. Market Estimates
        2. Market Estimates & Forecast,
        3. Market Estimates & Forecast, by Application,
        4. Middle East
        5. Africa
        6. Latin America
    10. COMPETITIVE LANDSCAPE
      1. Key Developments & Growth Strategies
      2. Competitor
      3. Vendor Share Analysis, 2022 (% Share)
    11. COMPANY PROFILES
      1. Microsoft (US)
        1. Company Overview
        2. Financial Overview
        3. Products Offered
        4. Key Developments
        5. SWOT Analysis
        6. Key Strategies
      2. IBM (US)
        1. Company Overview
        2. Products Offered
        3. Key Developments
        4. SWOT Analysis
        5. Key Strategies
      3. Google (US)
        1. Financial Overview
        2. Products Offered
        3. Key Developments
        4. SWOT Analysis
        5. Key Strategies
      4. Amazon (US)
        1. Company Overview
        2. Financial Overview
        3. Products Offered
        4. Key Developments
        5. SWOT Analysis
        6. Key Strategies
      5. John Deere(US)
        1. Company Overview
        2. Financial Overview
        3. Products Offered
        4. Key Developments
        5. SWOT Analysis
        6. Key Strategies
      6. CropX (Israel)
        1. Company Overview
        2. Financial Overview
        3. Products
        4. Key Developments
        5. SWOT Analysis
        6. Key
      7. Vision Robotics (US)
        1. Company Overview
        2. Products Offered
        3. Key Developments
        4. SWOT Analysis
        5. Key Strategies
      8. DroneDeploy (US)
        1. Company Overview
        2. Financial Overview
        3. Products
        4. Key Developments
        5. SWOT Analysis
        6. Key
      9. PrecisionHawk (US)
        1. Company Overview
        2. Products Offered
        3. Key Developments
        4. SWOT Analysis
        5. Key Strategies
      10. AGCO CorporationCompany
        1. Company Overview
        2. Financial Overview
        3. Products Offered
        4. Key Developments
        5. SWOT Analysis
        6. Key Strategies
    12. MARKET SYNOPSIS 19
    13. GLOBAL APPLIED AI IN AGRICULTURE MARKET, BY REGION, 2019–2032 (USD MILLION)
    14. NORTH AMERICA APPLIED AI IN AGRICULTURE MARKET, BY APPLICATION, 2019–2032
    15. CANADA APPLIED AI IN AGRICULTURE MARKET, BY OFFERING, 2019–2032 (USD MILLION)
    16. EUROPE APPLIED AI IN AGRICULTURE MARKET, BY COUNTRY, 2019–2032 (USD MILLION)
    17. UK APPLIED AI IN AGRICULTURE MARKET, BY OFFERING, 2019–2032 (USD MILLION)
    18. FRANCE APPLIED AI IN AGRICULTURE MARKET, BY TECHNOLOGY, 2019–2032 (USD
    19. SPAIN APPLIED AI IN AGRICULTURE MARKET, BY OFFERING, 2019–2032 (USD MILLION)
    20. REST OF EUROPE APPLIED AI IN AGRICULTURE MARKET, BY TECHNOLOGY, 2019–2032
    21. ASIA-PACIFIC APPLIED AI IN AGRICULTURE MARKET, BY COUNTRY, 2019–2032 (USD
    22. JAPAN APPLIED AI IN AGRICULTURE MARKET, BY OFFERING, 2019–2032 (USD MILLION)
    23. SOUTH KOREA APPLIED AI IN AGRICULTURE MARKET, BY TECHNOLOGY, 2019–2032
    24. REST OF ASIA-PACIFIC APPLIED AI IN AGRICULTURE MARKET, BY TECHNOLOGY, 2019–2032
    25. ACQUISITIONS/MERGERS 135
    26. MICROSOFT: KEY DEVELOPMENT 143
    27. IBM. : KEY DEVELOPMENT 147
    28. GOOGLE: KEY DEVELOPMENT 151
    29. AMAZON: KEY DEVELOPMENT 154
    30. PRECISIONHAWK: PRODUCTS OFFERED 172
    31. (USD MILLION) 56
    32. NORTH AMERICA APPLIED AI IN AGRICULTURE MARKET, BY APPLICATION, 2022 VS 2032
    33. (% SHARE) 64
    34. VS 2032 (USD MILLION) 65
    35. ASIA-PACIFIC APPLIED AI IN AGRICULTURE MARKET, BY APPLICATION, 2022 VS 2032 (USD
    36. VS 2032 (USD MILLION) 99
    37. AFRICA APPLIED AI IN AGRICULTURE MARKET, BY TECHNOLOGY, 2022 VS 2032 (USD MILLION)
    38. (USD MILLION) 101
    39. VS 2032 (USD MILLION) 119
    40. GLOBAL APPLIED AI IN AGRICULTURE MARKET: COMPETITIVE BENCHMARKING 123
    41. VENDOR SHARE ANALYSIS (2022) (%) 124
    42. AMAZON: SWOT ANALYSIS 132

    Applied AI in Agriculture Market Segmentation

    Market Segmentation Overview

    • Detailed segmentation data will be available in the full report
    • Comprehensive analysis by multiple parameters
    • Regional and country-level breakdowns
    • Market size forecasts by segment
    Infographic

    Free Sample Request

    Kindly complete the form below to receive a free sample of this Report

    Get Free Sample

    Customer Strories

    “I am very pleased with how market segments have been defined in a relevant way for my purposes (such as "Portable Freezers & refrigerators" and "last-mile"). In general the report is well structured. Thanks very much for your efforts.”

    Victoria Milne

    Founder
    Case Study
    Chemicals and Materials